Background Stroke is one of the most common neurological conditions that often leads to
upper limb motor impairments, significantly affecting individuals' quality of life. Rehabilitation …

With the development of brain-computer interfaces (BCI) technologies, EEG-based BCI
applications have been deployed for medical purposes. Motor imagery (MI), applied to …

Generalizing the electroencephalogram (EEG) decoding methods to unseen subjects is an
important research direction for realizing practical application of brain-computer interfaces …

The purpose of this study is to analyze the contribution of the interactions between
electrodes, measured either as correlation or as Jaccard distance, to the classification of two …

To apply EEG-based brain-machine interfaces during rehabilitation, separating various
tasks during motor imagery (MI) and assimilating MI into motor execution (ME) are needed …

In the classification of motor imagery Electroencephalogram (MI-EEG) signals through deep
learning models, challenges such as the insufficiency of feature extraction due to the limited …

Background: Hereditary spastic paraplegias (HSPs) are a group of inheritance diseases
resulting in gait abnormalities, which may be detected using instrumented gait analysis. The …

Motor imagery (MI) monitoring is crucial for targeted stroke rehabilitation. MI involves mental
simulation of motor actions, engaging areas like the motor cortex. Electroencephalography …

Lower limb motor dysfunction is a prevalent complication of stroke that significantly impacts
patients' quality of life. Current research indicates that motor imagery-based brain-computer …

This book gathers selected high-quality research papers presented at the Second
International Conference on Intelligent System (ICIS 2023), organized by Industrial …